journal article·2026-04Open access

Predicting Macrophage Spatial Localization from Single‐Cell Transcriptomes to Uncover Disease Mechanisms

Junping Yin, Qi Mei, Hans‐Joachim Paust, Ning Song, Yu Zhao, Daniela Klaus, Melanie Eichler, Yijun Hua, Jie Qin, Weiting Cheng, Christina K. Weisheit, Veronika Lukacs‐Kornek, Isis Ludwig‐Portugall, Sibylle von Vietinghoff, Christian F. Krebs, Johanna Klughammer, Ulf Panzer, Christian Kurts, Jian Li

Advanced Science· Volume 13· Issue 21

Abstract

Abstract When cells are isolated for single‐cell RNA sequencing (scRNA‐seq), their positional information is inevitably lost. Here, an algorithm termed MERLIN is described that can reconstruct such information in organs with compartmentalized anatomy, such as the kidney. Several independent immune cell scRNA‐seq datasets from three renal compartments were generated to train different machine learning algorithms. A modified multi‐layer Perceptron approach most accurately predicted positions of resident macrophages, best, achieving over 75% accuracy in both murine and human kidney datasets. More motile immune cells, like lymphocytes, were not predictable. Positional transcriptomic fingerprints were enriched in pathways of microenvironmental responses and cellular adaptation, and showed a sex bias. MERLIN also predicted positions of resident and recently recruited macrophages in a crescentic glomerulonephritis mouse model. Analysis of published scRNA‐seq datasets from endotoxin‐ and ischemia/reperfusion‐induced models of acute kidney injury revealed proinflammatory responses predominantly in outer medullary macrophages, consistent with the known pathology. Moreover, the response of cortical macrophages to commonly used therapies for diabetic nephropathy aligned with the known clinical drug efficacy. Finally, MERLIN was successfully trained to predict the spatial distribution of brain microglia. Together, MERLIN enables spatial interpretation of scRNA‐seq datasets in organs with defined anatomical regions and enhances mechanistic insights into disease processes.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Single-cell and spatial transcriptomics · Neuroinflammation and Neurodegeneration Mechanisms · Cell Image Analysis Techniques

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Institute of Molecular Medicine and Experimental Immunology (IMMEI) University Hospital Bonn 53127 Bonn Germany

Department of Oncology Tongji Hospital Tongji Medical College Huazhong University of Science and Technology Wuhan Hubei 430030 P. R. China

Cancer Center Shanxi Bethune Hospital Shanxi Academy of Medical Sciences Tongji Shanxi Hospital Third Hospital of Shanxi Medical University Taiyuan Shanxi 030006 P. R. China

III. Department of Medicine University Medical Center Hamburg‐Eppendorf 20249 Hamburg Germany

Renal Division Department of Medicine Beijing Anzhen Hospital Capital Medical University Beijing 100029 P. R. China

Department of Nasopharyngeal Carcinoma Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy Sun Yat‐sen University Cancer Center Guangzhou 510060 P. R. China

State Key Laboratory of Oncology in South China Sun Yat‐sen University Cancer Center Guangzhou 510060 P. R. China

Department of Obstetrics Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region Nanning 530000 P. R. China

Birth Defects Prevention and Control Institute Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region Nanning 530012 P. R. China

Cancer Center Renmin Hospital of Wuhan University Wuhan Hubei 430060 P. R. China

Department of Anesthesiology and Intensive Care Medicine University Hospital Bonn 53127 Bonn Germany

Nephrology Section Medical Clinic 1 University Hospital Bonn 53127 Bonn Germany

Hamburg Center for Translational Immunology University Medical Center Hamburg‐Eppendorf 20249 Hamburg Germany

Gene Center and Department of Biochemistry Ludwig‐Maximilians‐Universität München 80539 Munich Germany

Department of Microbiology and Immunology Doherty Institute for Infection and Immunity University of Melbourne Victoria 3000 Australia

Funding

Deutsche Forschungsgemeinschaft

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